Paper Title
SMART WHEELCHAIR CONTROL USING VOICE AND GESTURE CONTROL
Article Identifiers
Registration ID: IJNRD_311591
Published ID: IJNRD2601061
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Keywords
Smart Wheelchair, Assistive Technology, Voice Control, Gesture Control, ESP32, Embedded Systems, Human–Computer Interaction, Robotics, Healthcare Technology
Abstract
Assistive healthcare technologies are rapidly advancing with the integration of Artificial Intelligence, embedded systems, and human–computer interaction. Conventional wheelchairs require manual operation, which poses significant challenges for individuals with severe physical disabilities. Although powered wheelchairs exist, many lack intuitive control methods, affordability, and adaptability to user needs. To overcome these limitations, this project proposes the development of a SMART WHEELCHAIR CONTROL SYSTEM USING VOICE AND GESTURE CONTROL. The proposed system is designed to provide an intelligent and user-friendly mobility solution by enabling wheelchair control through voice commands and hand gestures. Voice recognition technology is used to capture and process spoken commands such as forward, backward, left, right, and stop, while gesture control allows navigation using predefined hand movements detected through sensors. The system is implemented using an ESP32 microcontroller, which offers built-in Wi-Fi and Bluetooth capabilities, high processing efficiency, low power consumption, and compact size. This makes the system cost-effective, portable, and suitable for real-time embedded applications. Motor driver circuits interface with DC motors to control wheelchair motion, while safety features such as obstacle detection and emergency stopping mechanisms enhance reliability and user safety. The modular architecture of the system allows seamless integration of voice and gesture control modules, enabling users to choose the most convenient mode of operation based on their physical abilities. The design is scalable and supports future enhancements such as smartphone-based control, health monitoring, GPS tracking, and AI-based navigation assistance. Experimental results indicate that the proposed smart wheelchair system significantly improves mobility independence, ease of use, and overall quality of life for physically challenged individuals. This project demonstrates the effectiveness of ESP32-based assistive technology in delivering an affordable, accessible, and intelligent mobility solution.
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How To Cite (APA)
GNANA SAGAR B N, MALATESH S H, KIRAN, DILIP G V, & AJAY KUMAR (January-2026). SMART WHEELCHAIR CONTROL USING VOICE AND GESTURE CONTROL. INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT, 11(1), a503-a505. https://ijnrd.org/papers/IJNRD2601061.pdf
Issue
Volume 11 Issue 1, January-2026
Pages : a503-a505
Other Publication Details
Paper Reg. ID: IJNRD_311591
Published Paper Id: IJNRD2601061
Research Area: Other area not in list
Author Type: Indian Author
Country: Bangalore, Karnataka, India
Published Paper PDF: https://ijnrd.org/papers/IJNRD2601061.pdf
Published Paper URL: https://ijnrd.org/viewpaperforall?paper=IJNRD2601061
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